Skip to main content
SpringerLink
Log in

Hey Alexa, What Should I Read? Comparing the Use of Social and Algorithmic Recommendations for Different Reading Genres

  • Conference paper
  • First Online:
Diversity, Divergence, Dialogue (iConference 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12645))

Included in the following conference series:

Abstract

Users often seek reading recommendations for what to read, across a variety of topics of interest and genres. While there has been extensive research on the development of recommender algorithms, our understanding of social factors relating to reading recommendation in the digital era is poor. We have no holistic view of how readers interact with diverse resources, social and digital, to obtain reading recommendations. Users can consult computer-generated summaries and human-created reviews. How much or how often the typical user relies on one or other source, or what variations there are by genre of intended reading, are both open questions.

To narrow these research gaps, we conducted a diary study to capture a comprehensive picture of readers’ use of algorithm- and social-sourced information to inform their future reading choices. Based on a qualitative analysis of these diaries, we produced a survey to investigate in-depth readers’ recommendation preferences across fictional reading, factual reading, academic resources, and news and articles. We show that users rely on different sources of recommendation information in different ways across different genres, and that modern social media plays an increasing role alongside established mass media, especially for fiction.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tewari, A.S., Kumar, A., Barman, A.G.: Book recommendation system based on combine features of content based filtering, collaborative filtering and association rule mining. In: 2014 IEEE International Advance Computing Conference (IACC), pp. 500–503. IEEE (2014)

    Google Scholar 

  2. Rosa, R.L., Rodriguez, D.Z., Bressan, G.: Music recommendation system based on user’s sentiments extracted from social networks. IEEE Trans. Consum. Electron. 61, 359–367 (2015)

    Article  Google Scholar 

  3. Subramaniyaswamy, V., Logesh, R., Chandrashekhar, M., Challa, A., Vijayakumar, V.: A personalised movie recommendation system based on collaborative filtering. Int. J. High Perform. Comput. Netw. 10, 54–63 (2017)

    Article  Google Scholar 

  4. Kenthapadi, K., Le, B., Venkataraman, G.: Personalized job recommendation system at linkedin: practical challenges and lessons learned. In: Proceedings of the Eleventh ACM Conference on Recommender Systems, pp. 346–347. Association for Computing Machinery (2017)

    Google Scholar 

  5. Park, D.H., Kim, H.K., Choi, I.Y., Kim, J.K.: A literature review and classification of recommender systems research. Expert Syst. Appl. 39, 10059–10072 (2012)

    Article  Google Scholar 

  6. Pearson, J., Owen, T., Thimbleby, H., Buchanan, G.R.: Co-reading: investigating collaborative group reading. In: The 12th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 325–334 (2012)

    Google Scholar 

  7. Cordón-García, J.-A., Alonso-Arévalo, J., Gómez-Díaz, R., Linder, D.: Social Reading: Platforms, Applications Clouds and Tags. Elsevier, Amsterdam (2013)

    Book  Google Scholar 

  8. Kutzner, K., Petzold, K., Knackstedt, R.: Characterising social reading platforms—a taxonomy-based approach to structure the field. In: 14th International Conference on Wirtschaftsinformatik (2019)

    Google Scholar 

  9. Ooi, K.: How adult fiction readers select fiction books in public libraries: a study of information-seeking in context. School of Information Management. Victoria University of Wellington (2008)

    Google Scholar 

  10. Huang, Z., Li, T., Xiao, S.: Research on library recommendation reading service system based on adaptive algorithm. Wirel. Pers. Commun. 102, 1963–1977 (2018)

    Article  Google Scholar 

  11. Cunningham, S.J.: How children find books for leisure reading: implications for the digital library. In: 11th Annual International ACM/IEEE Joint Conference on Digital Libraries, pp. 431–432. Association for Computing Machinery (2011)

    Google Scholar 

  12. Cunningham, S.J., Vanderschantz, N., Timpany, C., Hinze, A., Buchanan, G.: Social information behaviour in bookshops: implications for digital libraries. In: Aalberg, T., Papatheodorou, C., Dobreva, M., Tsakonas, G., Farrugia, C.J. (eds.) TPDL 2013. LNCS, vol. 8092, pp. 84–95. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40501-3_9

    Chapter  Google Scholar 

  13. Mathew, P., Kuriakose, B., Hegde, V.: Book recommendation system through content based and collaborative filtering method. In: 2016 International Conference on Data Mining and Advanced Computing (SAPIENCE), pp. 47–52. IEEE (2016)

    Google Scholar 

  14. Liu, J., Dolan, P., Pedersen, E.R.: Personalized news recommendation based on click behavior. In: Proceedings of the 15th International Conference on Intelligent User Interfaces, pp. 31–40. Association for Computing Machinery (2010)

    Google Scholar 

  15. Li, L., Wang, D., Li, T., Knox, D., Padmanabhan, B.: SCENE: a scalable two-stage personalized news recommendation system. In: Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 125–134. Association for Computing Machinery (2011)

    Google Scholar 

  16. Bulut, B., Kaya, B., Alhajj, R., Kaya, M.: A paper recommendation system based on user’s research interests. In: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 911–915. IEEE (2018)

    Google Scholar 

  17. Zulkarnain, T.D.P.: Proposed model of academic reading material recommendation system. In: The 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering 2020, pp. 105–109. Association for Computing Machinery (2020)

    Google Scholar 

  18. Seyednezhad, S., Cozart, K.N., Bowllan, J.A., Smith, A.O.: A review on recommendation systems: context-aware to social-based. arXiv preprint arXiv:1811.11866 (2018)

  19. Amri, C., Bambia, M., Faiz, R.: Behavior-based approach for user interests prediction. In: 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), pp. 541–548. IEEE (2017)

    Google Scholar 

  20. Chandak, M., Girase, S., Mukhopadhyay, D.: Introducing hybrid technique for optimization of book recommender system. Procedia Comput. Sci. 45, 23–31 (2015)

    Article  Google Scholar 

  21. Hu, J., Shao, H., Tang, J., Zhang, S.: Research on reading subject recommendation of library based on data analysis. J. Phys: Conf. Ser. 1607, 012022 (2020)

    Google Scholar 

  22. Kanetkar, S., Nayak, A., Swamy, S., Bhatia, G.: Web-based personalized hybrid book recommendation system. In: 2014 International Conference on Advances in Engineering & Technology Research (ICAETR-2014), pp. 1–5. IEEE (2014)

    Google Scholar 

  23. Sachan, A., Richariya, V.: A survey on recommender systems based on collaborative filtering technique. Int. J. Innovations Eng. Technol. (IJIET) 2, 8–14 (2013)

    Google Scholar 

  24. Mooney, R.J., Roy, L.: Content-based book recommending using learning for text categorization. In: Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 195–204. Association for Computing Machinery (2000)

    Google Scholar 

  25. Kompan, M., Bieliková, M.: Content-based news recommendation. In: Buccafurri, F., Semeraro, G. (eds.) EC-Web 2010. LNBIP, vol. 61, pp. 61–72. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15208-5_6

    Chapter  Google Scholar 

  26. Wang, N., Zhao, H., Zhu, X., Li, N.: The review of recommendation system. In: Xie, Y., Zhang, A., Liu, H., Feng, L. (eds.) GSES 2018. CCIS, vol. 980, pp. 332–342. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-7025-0_34

    Chapter  Google Scholar 

  27. Rafsanjani, A.H.N., Salim, N., Aghdam, A.R., Fard, K.B.: Recommendation systems: a review. Int. J. Comput. Eng. Res. 3, 47–52 (2013)

    Google Scholar 

  28. Shardanand, U., Maes, P.: Social information filtering: algorithms for automating “word of mouth”. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 210–217. ACM Press/Addison-Wesley Publishing Co. (1995)

    Google Scholar 

  29. Smith, B., Linden, G.: Two decades of recommender systems at Amazon.com. IEEE Internet Comput. 21, 12–18 (2017)

    Google Scholar 

  30. Ghazanfar, M.A., Prugel-Bennett, A.: A scalable, accurate hybrid recommender system. In: 2010 Third International Conference on Knowledge Discovery and Data Mining, pp. 94–98. IEEE (2010)

    Google Scholar 

  31. Gao, Q., Dong, A.: A conditional context-awareness ontology based personalized recommendation approach for e-reading. In: 2017 First IEEE International Conference on Robotic Computing (IRC), pp. 365–370. IEEE (2017)

    Google Scholar 

  32. Saricks, J.G.: Readers’ Advisory Service in the Public Library. American Library Association, Chicago (2005)

    Google Scholar 

  33. Spiteri, L.F., Pecoskie, J., Tarulli, L.: In the readers’ own words: how user content in the catalog can enhance readers’ advisory services. Ref. User Serv. Quart. 56, 91–95 (2016)

    Article  Google Scholar 

  34. Mohr, K.A.: Children’s choices for recreational reading: a three-part investigation of selection preferences, rationales, and processes. J. Literacy Res. 38, 81–104 (2006)

    Article  Google Scholar 

  35. Rehberg Sedo, D.: Richard and Judy’s Book Club and ‘Canada Reads’: Readers, books and cultural programming in a digital era. Inf. Community Soc. 11, 188–206 (2008)

    Article  Google Scholar 

  36. Hall, R.M.: The “Oprahfication” of literacy: reading “Oprah’s book club.” Coll. Engl. 65, 646–667 (2003)

    Article  Google Scholar 

  37. Makri, S., Chen, Y.-C., McKay, D., Buchanan, G., Ocepek, M.: Discovering the unfindable: the tension between findability and discoverability in a bookshop designed for serendipity. In: Lamas, D., Loizides, F., Nacke, L., Petrie, H., Winckler, M., Zaphiris, P. (eds.) INTERACT 2019. LNCS, vol. 11747, pp. 3–23. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-29384-0_1

    Chapter  Google Scholar 

  38. Barnett, T.: Social reading: the Kindle’s social highlighting function and emerging reading practices. Aust. Humanit. Rev. 56, 141–162 (2014)

    Google Scholar 

  39. Nakamura, L.: “Words with friends”: socially networked reading on Goodreads. PMLA 128, 238–243 (2013)

    Google Scholar 

  40. Lommatzsch, A.: Real-time news recommendation using context-aware ensembles. In: de Rijke, M., et al. (eds.) ECIR 2014. LNCS, vol. 8416, pp. 51–62. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06028-6_5

    Chapter  Google Scholar 

  41. Pu, P., Chen, L., Hu, R.: A user-centric evaluation framework for recommender systems. In: Proceedings of the fifth ACM Conference on Recommender Systems, pp. 157–164. Association for Computing Machinery (2011)

    Google Scholar 

  42. Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22, 5–53 (2004)

    Article  Google Scholar 

  43. Sinha, R.R., Swearingen, K.: Comparing recommendations made by online systems and friends. DELOS 106 (2001)

    Google Scholar 

  44. Preece, J., Sharp, H., Rogers, Y.: Interaction Design: Beyond Human-Computer Interaction. Wiley, Hoboken (2015)

    Google Scholar 

  45. Lazar, J., Feng, J.H., Hochheiser, H.: Research Methods in Human-Computer Interaction. Morgan Kaufmann, Burlington (2017)

    Google Scholar 

  46. Flick, U.: An Introduction to Qualitative Research. Sage, Thousand Oaks (2018)

    Google Scholar 

  47. Rowlands, I., Nicholas, D.: Understanding information behaviour: how do students and faculty find books? J. Acad. Librariansh. 34, 3–15 (2008)

    Article  Google Scholar 

  48. Mascheroni, G., Ólafsson, K.: The mobile Internet: access, use, opportunities and divides among European children. New Media Soc. 18, 1657–1679 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. iSchool, University of Melbourne, Parkville, VIC, 3010, Australia

    Huiwen Zhang, George Buchanan & Dana McKay

Authors
  1. Huiwen Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. George Buchanan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dana McKay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to George Buchanan .

Editor information

Editors and Affiliations

  1. Humboldt University of Berlin, Berlin, Germany

    Katharina Toeppe

  2. Renmin University of China, Beijing, China

    Hui Yan

  3. The University of Hong Kong, Hong Kong, Hong Kong

    Samuel Kai Wah Chu

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, H., Buchanan, G., McKay, D. (2021). Hey Alexa, What Should I Read? Comparing the Use of Social and Algorithmic Recommendations for Different Reading Genres. In: Toeppe, K., Yan, H., Chu, S.K.W. (eds) Diversity, Divergence, Dialogue. iConference 2021. Lecture Notes in Computer Science(), vol 12645. Springer, Cham. https://doi.org/10.1007/978-3-030-71292-1_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-71292-1_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-71291-4

  • Online ISBN: 978-3-030-71292-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation